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Shows whether the association in a contingency table is statistically significant.
Examples are Cramer’s phi and the correlation coefficient.
Replacing missing values in data analysis by estimating values from the available data.
Graphic depiction of a bivariate distribution.
The value or category in a distribution with the highest frequency.
Documentation for a data file that usually contains the question wording and responses codes for each variable.
The middle value in a distribution.
A graphic display of a univariate distribution.
Indicates how much the dependent variable changes for every one-unit increase in the independent variable.
The most commonly used statistical measure of variation.
The numerical difference between an observed value and the value predicted by the regression line.
Consists of editing, coding, data entry, and data cleaning.